Benchmark Radar: A Living Database and Search Engine for AI Benchmarks and Evaluation
Benchmark researchers and developers of large language models (LLMs) and other AI systems need to find relevant evaluations, locate their benchmark datasets and code, and understand the settings behind reported scores. We present Benchmark Radar, a living database and search engine for retrieval and discovery of AI benchmarks, covering LLM evaluation, agentic and tool-use bench
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Benchmark researchers and developers of large language models (LLMs) and other AI systems need to find relevant evaluations, locate their benchmark datasets and code, and understand the settings behind reported scores. We present Benchmark Radar, a living database and search engine for retrieval and discovery of AI benchmarks, covering LLM evaluation, agentic and tool-use bench
As an ML engineer, understanding and selecting appropriate benchmarks is crucial for evaluating model performance, identifying biases, and ensuring responsible AI development. This tool streamlines the discovery of relevant benchmarks, saving significant time and effort in the evaluation phase of the ML lifecycle.